Study of Generative Adversarial Networks for Acoustic Signal Enhancement: A Review

Abstract

Acoustic signals enhancement is an important research topic. It has many applications like cochlear implants, speech and speaker recognition, hearing aids, mobile phones etc. The signals processed by these system are always susceptible to noises. Hence, algorithms are required to extract clean signal from noisy ones. Nowadays , deep neural network are the most sought after tool for signal enhancement. Generative Adversarial Network(GAN) is also one of the recent approaches applied to signal enhancement domain. More work is performed by GANs in image and video processing. To the best of my knowledge no review work on the usage of GANs for acoustic signal enhancement have been done. This paper is a review on the use of GANs for acoustical signals enhancement where speech signal is used as acoustic signal. The paper provides in a summarized manner about the basic GAN architectures and its limitations, feature sets used as input to GAN, limitations, performance evaluation measures and future directions.